5 Conclusion, Limitations, and Future Scope -- References -- Review of Classification and Detection for Insects/Pests Using Machine Learning and Deep Learning Approach -- 1 Introduction -- 1.1 Pictorial Representation of Classification and Detection of Pests and Comparison Between ML and DL -- 2 Material -- 2.1 Dataset Collection -- 3 Literature Work -- 3.1 Review of Different Machine Learning and Deep Learning Techniques for the Classification of Pests -- 4 Conclusion -- References -- Sentiment Analysis of Product Reviews Using Deep Learning and Transformer Models: A Comparative Study -- 1 Introduction -- 2 Literature Review -- 3 Sentiment Analysis -- 3.1 Sentiment Analysis Based on Machine Learning -- 3.2 Sentiment Analysis Based on Deep Learning -- 3.3 Sentiment Analysis Based on Transformer-Based Models -- 4 Implementation -- 4.1 Dataset -- 4.2 Data Pre-processing -- 4.3 Classification Models -- 5 Results and Discussions -- 5.1 Hyper Parameters Used -- 5.2 Performance Evaluation -- 6 Conclusion -- References -- Effect of Variation in Pause Times Over MANET Routing Protocols -- 1 Introduction -- 2 MANET Routing Protocols and Literature Review -- 3 Environment Setup -- 4 Performance Metrics -- 5 Conclusions and Future Scope -- References -- DDCMR2: A Deep Detection and Classification Model with Resizing and Rescaling for Plant Disease -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology and Implementation -- 3.1 Data Collection -- 3.2 Data Cleaning, Preprocessing, and Visualization -- 3.3 Cache, Shuffle, and Prefetch -- 3.4 Model Building -- 3.5 Hyperparameters Choice -- 4 Results and Discussion -- 5 Conclusion and Future Scope -- References -- Leveraging Natural Language Queries for Effective Video Analysis -- 1 Introduction -- 2 Related Work -- 3 Methodology and Models -- 3.1 Uni-Modal Encoder -- 3.2 Cross-Modal Encoder. |